Adaptive Digital’s HD AEC acoustic echo cancellation technology can be found in a wide range of applications, like IP Intercom Systems, Conference Speakerphones for both large and small conference rooms/huddle rooms, IP Desk Phones, Mobile Handsets, Radio over IP, and essentially anywhere where voice quality is affected by adverse room conditions. Additionally, the HD AEC acoustic echo canceller is effective in improving the performance of speech recognition algorithms when operating in an echoic environments.

HD AEC ARM Cortex-M7

CPU Utilization & Memory Requirements All Memory usage is given in units of byte.

Platform

Sampling Rate

Tail Length (msec)

MIPS*per Mic

Per Channel Memory

Cortex-M7

8 kHz

32

26

47k

64

28

50k

128

30

57k

256

34

65k

Cortex-M7

16 kHz

32

53

50k

64

56

57k

128

64

65k

256

79

96k

* with Anti-howling

Texas Instruments

HD AEC ARM C674x

CPU Utilization & Memory Requirements All Memory usage is given in units of byte.

Platform

Sampling Rate

Tail Length (msec)

MIPS* per Mic

Per Channel Memory

C674x

8 kHz

32

19

25k

64

20

34k

128

21

55k

256

22

110k

320

24

143k

400

62

160k

C674x

16 kHz

32

33

45k

64

34

61k

128

36

96k

256

38

180k

320

43

223k

400

48

250k

C674x

32 kHz

32

65

56k

64

67

86k

128

71

157k

256

77

350k

320

81

470k

400

85

470k

C674x

48 kHz

32

78

68k

64

103

114k

128

111

234k

256

125

584k

320

133

814k

400

141

1100k

* with Anti-howling

Note: MIPS generated with single mic enabled, and running with on chip (internal) program and data memory only. When using external source for program and data memory, MIPS increase by 3x per enabled microphone.

HD AEC ARM C64x / C64x+

CPU Utilization & Memory Requirements All Memory usage is given in units of byte.

Platform

Sampling Rate

Tail Length (msec)

MIPS* per Mic

Per Channel Memory

C64x / C64x+

8 kHz

32

22

30k

64

27

45k

128

35

81k

256

51

179k

320

57

240k

400

63

300k

C64x / C64x+

16 kHz

32

43

54k

64

51

80k

128

67

140k

256

101

282k

320

119

365k

400

150

450k

C64x / C64x+

32 kHz

32

85

75k

64

103

128k

128

136

259k

256

204

620k

320

238

847k

400

300

1000k

C64x / C64x+

48 kHz

32

110

99k

64

132

185k

128

188

410k

256

290

1085k

320

—

—

400

342

1534k

* with Anti-howling

Note: MIPS generated with single mic enabled, and running with on chip (internal) program and data memory only. When using external source for program and data memory, MIPS increase by 3x per enabled microphone.

HD AEC ARM C55x

CPU Utilization & Memory Requirements All Memory usage is given in units of byte.

HD AEC ARM Windows/Linux 32 Bit*

CPU Utilization & Memory Requirements All Memory usage is given in units of byte. *Contact Sales for 64 Bit numbers.

Platform

Sampling Rate

Tail Length (msec)

MIPS* per Mic

Per Channel Memory

Windows/Linux

8 kHz

32

81

28k

64

92

37k

128

127

58k

256

186

113k

320

220

147k

400

262

195k

Windows/x86

16 kHz

32

160

52k

64

194

68k

128

248

104k

256

373

187k

320

429

235k

400

506

301k

Windows/x86

32 kHz

32

821

56k

64

1089

86k

128

1409

157k

256

2284

350k

320

2489

470k

400

2702

600k

Windows/x86

48 kHz

32

1266

68k

64

103

114k

128

1913

234k

256

2966

584k

320

3493

814k

400

1400

1004k

* with Anti-howling

Note: MIPS generated with single mic enabled, and running with on chip (internal) program and data memory only. When using external source for program and data memory, MIPS increase by 3x per enabled microphone.

Demos

HD AEC: Get the demos

First Name

Last Name

Company

What is your application / target equipment (VoIP, PBX, etc.)?

Information

Email

Demo request form will put you in contact with our sales team. They will supply you with a complete list of hardware requirements. Demo/Eval agreement will be required to download the software. Thank you for your interest!

Adaptive Digital Technologies’ high definition acoustic echo canceller (HD AEC), has integrated Noise Reduction and AGC into its AEC algorithm and created appropriate hooks to make them work together seamlessly.

NOISE REDUCTION

Noise Reduction is done pre-NLP, resulting in a far cleaner audio stream feeding into the non-linear processor. By making the AGC aware of the AEC state, we can avoid having the AGC becoming a cause of howling. Changes in gain can adversely affect an AEC; Adaptive Digital’s HD AEC has the ability to adapt to changes in the acoustic path (including gain/loss changes.) And when the changes are known, like in the case of controlled gain changes, Adaptive Digital’s HD AEC has hooks that enable the application to tell it the nature of the gain change so it can adjust immediately rather than take time to reconverge.

AUTO GAIN CONTROL

Automatic Gain Control (AGC) is provided to help boost lower level speech signals in hands-free environments. The AGC algorithm is used to automatically adjust the speech level of an audio signal so that the level falls within a user-defined output level range.

ANTI-HOWLING

Howling can occur when there is a full-duplex communication link with echo at both ends. These echo, or coupling, paths create feedback loops. In full-duplex communication systems where, by definition, both communication paths are open at all time, howling can be a serious issue. With Anti-howling enabled the HD AEC identifies when instability is starting to occur and takes action to mitigate the instance of feedback looping. HD AEC electronically removes both direct coupling and reflected echo, enabling true full-duplex hands-free telephony.

FAST CONVERGENCE and RECONVERGENCE

Convergence time is the time it takes the echo cancel algorithm to analyze the signal. This number can never be “0” as analyzing the signal is a critical part of the echo cancellation process. Adaptive Digital’s HD AEC analyses the signal in as finite a period as is possible to best develop the echo model, and then cancels the echo immediately.

DOUBLE-TALK

Superior Double-talk performance. Double talk occurs when the speech of two talkers overlap causing the audio signals to arrive simultaneously at the echo canceller. Detection of double-talk is vital to the performance of an acoustic echo canceller.

HD AEC VARIANTS

Single microphone (standard), Multi-microphone , and

Dual-microphone with Noise Reduction.

Single-microphone is used in most applications. Multi-microphone is used in applications such as high-end conference phones that make use of multiple microphones that are placed around conference room table. Dual-microphone with noise reduction is used in devices that have a primary microphone to capture speech and a secondary microphone that is used to measure background noise.

USER CONTROLLED PARAMETERS (SUMMARY)

Sampling Rate

Tail Length

Frame Size

NLP Control

AGC Control

Equalizer Control

Noise Reduction Control

Howling Control

Functional Description

The figure below is a simplified block diagram of the HD Acoustic Echo Canceller.

The top half of the diagram shows the receive signal path, or the signal path from the telephone network to the speaker. The bottom half of the diagram shows the transmit signal path from the microphone toward the telephone network. The HD AEC cancels the echo that occurs between the speaker output and the microphone input.

The terms Rx (Receive) and Tx (Transmit) may be confusing at first because both the receive and transmit paths have inputs and outputs. The names receive and transmit are used from the point-of-view of the person at the speaker/microphone side.The RxIn signal coming from the network is fed into the RxNLP (Receive Nonlinear Processor). Under difficult acoustic conditions, the RxNLP can improve full-duplex operation and hence the overall voice quality.The output of the RxNLP is fed both to the transmit output (TxOut) and into the bulk delay block. The bulk delay block compensates for the buffering delay at the RxOut and TxIn interfaces as well as any other non-acoustic system delays in the path between RxOut and TxIn. The output of the bulk delay is fed to the adaptive filter.The adaptive filter estimates the echo and subtracts it from the TxIn signal to form the residual signal.The residual signal is fed to the noise reduction block. This noise reduction block removes background noise and therefore improves the signal to noise ratio of the transmit signal.The adaptive filter works in conjunction with the bulk delay monitor, which monitors and adjusts bulk delay in situations where the bulk delay is unknown due non-deterministic audio drivers.The output of the noise reduction block is fed into an equalizer. The equalizer is used to flatten out the frequency response of the transmit channel. This may be necessary due to the acoustics of the hands-free device and due to the characteristics of the microphone itself.The output of the transmit equalizer is fed into the transmit non-linear processor (TxNLP). The TxNLP increases the echo attenuation by attenuating the residual by a variable amount based upon the talk state. The TxNLP block also includes a comfort noise generator.Automatic Gain Control (AGC) is provided to help boost lower level speech signals in hands-free environments. The compute gain block computes the AGC gain. The output of the TxNLP is fed into the AGC gain block, which provides gain or loss depending upon the residual signal level. The output of the AGC is fed to the TxOut output of the AEC.In the multi-microphone case, there is still a single receive path but there is one transmit path per microphone.
In the case of multi-microphone noise reduction, there is a single receive path, a complete transmit path for the primary microphone, and a partial transmit path for the secondary microphone. In this case, there are two transmit inputs (one for each microphone) but only one transmit output containing the echo cancelled and noise reduced signal.

Significant Upgrades

"We have made significant changes to our core algorithm in order to boost efficiency. HD AEC operate in a higher audio bandwidth. We have improved implementation by simplifying and providing straight forward API."